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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Direct numerical simulations of reacting flows with detailed chemistry using many-core/GPU acceleration

A new direct numerical simulation (DNS) code for multi-component gaseous reacting flows has been developed at KAUST, with the state-of-the-art programming model for next generation high performance computing platforms. The code, named KAUST Adaptive Reacting Flows Solver (KARFS), employs the MPI+X programming, and relies on Kokkos for “X” for performance portability to multi-core, many-core and GPUs, providing innovative software development while maintaining backward compatibility with established parallel models and legacy code. The capability and potential of KARFS to perform DNS of reacting flows with large, detailed reaction mechanisms is demonstrated with various model problems involving ignition and turbulent flame propagations with varying degrees of chemical complexities.

Computer Science↗
DOE OSTI2014

NP2010: An Assessment and Outlook for Nuclear Physics

This grant provided partial support for the National Research Council’s (NRC) decadal survey of nuclear physics. This is part of NRC’s larger effort to assess and discuss the outlook for different fields in physics and astronomy, Physics 2010, which takes place approximately every ten years. A report has been prepared as a result of the study that is intended to inform those who are interested about the current status of research in this area and to help guide future developments of the field. A pdf version of the report is available for download, for free, at http://www.nap.edu/catalog.php?record_id=13438. Among the principal conclusions reached in the report are that the nuclear physics program in the United States has been especially well managed, principally through a recurring long-range planning process conducted by the community, and that current opportunities developed pursuant to that planning process should be exploited. In the section entitled “Building the Foundation for the Future,” the report notes that attention needs to be paid to certain elements that are essential to the continued vitality of the field. These include ensuring that education and research at universities remain a focus for funding and that a plan be developed to ensure that forefront-computing resources, including exascale capabilities when developed, be made available to nuclear science researchers. The report also notes that nimbleness is essential for the United States to remain competitive in a rapidly expanding international nuclear physics arena and that streamlined and flexible procedures should be developed for initiating and managing smaller-scale nuclear science projects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Mesoscale Modeling of Hydrogels Under Frictional Shear Stress

Hydrogels are three-dimensional networks of hydrophilic polymers often used as a simplified model of hydrated biological materials, from cartilaginous joints to the ocular tear film. However, the lubrication mechanisms of hydrogels remain poorly understood, partly due to their complex polymeric structure, which creates blurred interfaces during sliding that are challenging to study experimentally. In this study, we employ dissipative particle dynamics (DPD) to investigate the frictional behavior of a polymeric hydrogel network sliding against a solid wall in an explicit viscous solvent. This computational approach enables us to model hydrodynamic interactions and mesoscale polymer dynamics, capturing key aspects of hydrogel friction. Our simulations reveal that hydrogel friction is governed by the interplay between polymer relaxation and viscous shear, characterized by the Weissenberg number (Wi). At low Wi, friction coefficient remain nearly constant, dominated by polymer relaxation. However, at higher Wi, friction is dominated by viscous drag within a near-wall solvent layer, leading to a linear increase in friction coefficient with Wi. Furthermore, our results demonstrate an inverse relationship between the friction coefficient and the applied normal load, consistent with experimental observations. This work provides new insights into the fundamental tribological properties of hydrogels, shedding light on the micromechanics of hydrogel friction. Improving our understanding of hydrogel structure and dynamics under friction advances our knowledge of the mechanisms regulating biological lubrication in health and disease.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Twisted fracton models in three dimensions

We study novel three-dimensional gapped quantum phases of matter which support quasiparticles with restricted mobility, including immobile “fracton” excitations. So far, most existing fracton models may be instructively viewed as generalized Abelian lattice gauge theories. Here, by analogy with Dijkgraaf-Witten topological gauge theories, we discover a natural generalization of fracton models, obtained by twisting the gauge symmetries. Introducing generalized gauge transformation operators carrying an extra phase factor depending on local configurations, we construct a plethora of exactly solvable three-dimensional models, which we dub “twisted fracton models.” A key result of our approach is to demonstrate the existence of rich non-Abelian fracton phases of distinct varieties in a three-dimensional system with finite-range interactions. For an accurate characterization of these novel phases, the notion of being inextricably non-Abelian is introduced for fractons and quasiparticles with one-dimensional mobility, referring to their new behavior of displaying braiding statistics that is, and remains, non-Abelian regardless of which quasiparticles with higher mobility are added to or removed from them. We also analyze these models by embedding them on a 3-torus and computing their ground-state degeneracies, which exhibit a surprising and novel dependence on the system size in the non-Abelian fracton phases. Furthermore, as an important advance in the study of fracton order, we develop a general mathematical framework which systematically captures the fusion and braiding properties of fractons and other quasiparticles with restricted mobility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Comparing the DES-SN5YR and Pantheon+ SN cosmology analyses: investigation based on ‘evolving dark energy or supernovae systematics’?

Recent cosmological analyses measuring distances of type Ia supernovae (SNe Ia) and baryon acoustic oscillations (BAO) have all given similar hints at time-evolving dark energy. To examine whether underestimated SN Ia systematics might be driving these results, Efstathiou (2025) compared overlapping SN events between Pantheon+ and DES-SN5YR (20 per cent SNe are in common), and reported evidence for an $\sim$0.04 mag offset between the low- and high-redshift distance measurements of this subsample of events. If this offset is arbitrarily subtracted from the entire DES-SN5YR sample, the preference for evolving dark energy is reduced. In this paper, we show that this offset is mostly due to different corrections for Malmquist bias between the two samples; therefore, an object-to-object comparison can be misleading. Malmquist bias corrections differ between the two analyses for several reasons. First, DES-SN5YR used an improved model of SN Ia luminosity scatter compared to Pantheon+ but the associated scatter-model uncertainties are included in the error budget. Secondly, improvements in host mass estimates in DES-SN5YR also affected SN standardized magnitudes and their bias corrections. Thirdly, and most importantly, the selection functions of the two compilations are significantly different, hence the inferred Malmquist bias corrections. Even if the original scatter model and host properties from Pantheon+ are used instead, the evidence for evolving dark energy from CMB, DESI BAO Year 1 and DES-SN5YR is only reduced from 3.9$\sigma$ to 3.3$\sigma$, consistent with the error budget. Finally, in this investigation, we identify an underestimated systematic uncertainty related to host galaxy property uncertainties, which could increase the final DES-SN5YR error budget by 3 per cent. In conclusion, we confirm the validity of the published DES-SN5YR results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Computing for the DUNE Long-Baseline Neutrino Oscillation Experiment

This is a talk given at Computers in High Energy Physics in Adelaide, South Australia, Australia in November 2019. It is partially intended to explain the context of DUNE Computing for computing specialists. The DUNE collaboration consists of over 180 institutions from 33 countries. The experiment is in preparation now with commissioning of the first 10kT fiducial volume Liquid Argon TPC expected over the period 2025-2028 and a long data taking run with 4 modules expected from 2029 and beyond. An active prototyping program is already in place with a short test beam run with a 700T, 15,360 channel prototype of single-phase readout at the neutrino platform at CERN in late 2018 and tests of a similar sized dual-phase detector scheduled for mid-2019. The 2018 test beam run was a valuable live test of our computing model. The detector produced raw data at rates of up to ~2GB/s. These data were stored at full rate on tape at CERN and Fermilab and replicated at sites in the UK and Czech Republic. In total 1.2 PB of raw data from beam and cosmic triggers were produced and reconstructed during the six week test beam run. Baseline predictions for the full DUNE detector data, starting in the late 2020's are 30-60 PB of raw data per year. In contrast to traditional HEP computational problems, DUNE's Liquid Argon TPC data consist of simple but very large (many GB) 2D data objects which share many characteristics with astrophysical images. This presents opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Seismicity on the western Greenland Ice Sheet: Surface fracture in the vicinity of active moulins

We analyzed geophone and GPS measurements collected within the ablation zone of the western Greenland Ice Sheet during a ~35 day period of the 2011 melt season to study changes in ice deformation before, during, and after a supraglacial lake drainage event. During rapid lake drainage, ice flow speeds increased to ~400% of winter values, and icequake activity peaked. At times >7 days after drainage, this seismicity developed variability over both diurnal and longer periods (~10 days), while coincident ice speeds fell to ~150% of winter values and showed nightly peaks in spatial variability. Approximately 95% of all detected seismicity in the lake basin and its immediate vicinity was triggered by fracture propagation within near-surface ice (<330 m deep) that generated Rayleigh waves. Icequakes occurring before and during drainage frequently were collocated with the down flow (west) end of the primary hydrofracture through which the lake drained but shifted farther west and outside the lake basin after the drainage. We interpret these results to reveal vertical hydrofracture opening and local uplift during the drainage, followed by enhanced seismicity and ice flow on the downstream side of the lake basin. This region collocates with interferometric synthetic aperture radar-measured speedup in previous years and could reflect the migration path of the meltwater supplied to the bed by the lake. The diurnal seismic signal can be associated with nightly reductions in surface melt input that increase effective basal pressure and traction, thereby promoting elevated strain in the surficial ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**

When choosing experimental conditions, Bayesian statistical tools can predict the experimental choices which will yield the highest information gain. Experimental choices could be temperature, pressure, reaction time, number of measurements, reactor volume, etc.. Three example analyses are presented here, each using the software Chemical Kinetics Parameter Estimation and Uncertainty Quantification (CheKiPEUQ). Information gain is a measure of reduction of uncertainty in a model's parameters. The three chemical system examples presented each illustrate Bayesian Design of Experiments using information gain. In the first chemical example, temperature selection impacts the information gain for the free energy of reaction in a two-component equilibrium reaction. In the second example, temperature and pressure are explored for a competitive adsorption Langmuir replacement reaction system. Finally, the third example is a catalytic membrane reactor which is a culmination of the previous examples. The catalytic membrane reactor has a complex and nonlinear response in the observables which is solved by numerical evaluation. In the three examples, the experimental conditions are treated as design variables for maximizing information gain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Three Regimes of Polymer Surface Dynamics under Crowded Conditions

In this work, single-molecule tracking was used to characterize the mobility of poly(ethylene glycol) chains at a solid–liquid interface over a wide range of surface coverage. Trajectories exhibited intermittent motion consistent with a generalized continuous time random walk (CTRW) model, where strongly confined “waiting times” alternated with rapid flights. The presence of three characteristic regimes emerged as a function of surface coverage, based on an analysis of effective short-time diffusion coefficients, mean-squared displacement, and CTRW distributions. The dilute “site-blocking” regime exhibited increasing short-time diffusion, less confined behavior, and shorter waiting times with higher surface coverage, as anomalously strong adsorption sites were increasingly passivated. At intermediate values of surface coverage, the “crowding” regime was distinguished by the exact opposite trends (slower, more confined mobility), presumably due to increasing intermolecular interactions. The trends reversed yet again in the “brush” regime, where adsorbing molecules interacted weakly with a layer of extended overlapping chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Simulations of multi-contrast x-ray imaging using near-field speckles

X-ray dark-field and phase-contrast imaging using near-field speckles is a novel technique that overcomes limitations inherent in conventional absorption x-ray imaging, i.e. poor contrast for features with similar density. Speckle-based imaging yields a wealth of information with a simple setup tolerant to polychromatic and divergent beams, and simple data acquisition and analysis procedures. Here, we present a simulation software used to model the image formation with the speckle-based technique, and we compare simulated results on a phantom sample with experimental synchrotron data. Thorough simulation of a speckle-based imaging experiment will help for better understanding and optimising the technique itself.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Cr/B{sub 4}C multilayer mirrors: Study of interfaces and X-ray reflectance

We present an experimental study of the effect of layer interfaces on the x-ray reflectance in Cr/B{sub 4}C multilayer interference coatings with layer thicknesses ranging from 0.7 nm to 5.4 nm. The multilayers were deposited by magnetron sputtering and by ion beam sputtering. Grazing incidence x-ray reflectometry, soft x-ray reflectometry, and transmission electron microscopy reveal asymmetric multilayer structures with a larger B{sub 4}C-on-Cr interface, which we modeled with a 1–1.5 nm thick interfacial layer. Reflectance measurements in the vicinity of the Cr L{sub 2,3} absorption edge demonstrate fine structure that is not predicted by simulations using the currently tabulated refractive index (optical constants) values for Cr.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The response of a fast scintillator screen (YAP:Ce) to low energy ions (0-40 keV) and its use to detect fast-ion-loss in stellarator TJ-II

A systematic study of scintillation materials was undertaken to improve the time resolution of the fast ion diagnostic currently installed at TJ-II stellarator. It was found that YAP:Ce (formula YAlO{sub 3}:Ce, Yttrium Aluminum Perovskite doped with Cerium) ionoluminescence offers better sensitivity and time response compared to the standard detector material, SrGa{sub 2}S{sub 4}:Eu (TG-Green), currently used in TJ-II. A comparison between both materials was carried out by irradiating them with H{sup +} ions of up to 40 keV using a dedicated laboratory setup. It is found that for the low energy ions of interest at TJ-II, YAP:Ce offers 20 times higher sensitivity than TG-Green and much faster decay time, 27 ns versus 540 ns. It is expected that the use of YAP:Ce in combination with a faster data acquisition and an ion counting software as part of the TJ-II ion luminescent probe will provide 20 times faster data on ion loss.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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